Preference for Sons in the US: Evidence from Business Names

24 Nov

I estimate preference for passing on businesses to sons by examining how common words son and sons are compared to daughter and daughters in the names of businesses.

In the US, all businesses have to register with a state. And all states provide a way to search business names, in part so that new companies can pick names that haven’t been used before.

I begin by searching for son(s) and daughter in states’ databases of business names. But the results of searching son are inflated because of three reasons:

  • son is part of many English words, from names such as Jason and Robinson to ordinary English words like mason (which can also be a name). 
  • son is a Korean name.
  • some businesses use the wordson playfully. For instance, sonis a homonym of sun and some people use that to create names like son of a beach.

I address the first concern by using a regex that only looks at words that exactly match son or sons. But not all states allow for regex searches or allow people to download a full set of results. Where possible, I try to draw a lower bound. But still some care is needed in interpreting the results.

Data and Scripts: https://github.com/soodoku/sonny_side

In all, I find that a conservative estimate of son to daughter ratio is between 4 to 1 to 26 to 1 across states.

Missing Women on the Streets of Delhi

19 Nov

In 1990, Amartya Sen estimated that more than 100 million women were missing in South and West Asia, and China. His NYRB article shed light on sex-discrimination in parts of Asia, highlighting, among other things, pathologies like sex-selective abortion, biases in nutrition, healthcare, and schooling.

We aim to extend that line of inquiry, and shed light on the question: “How many women are missing from a public life?” In particular, we aim to answer how many women are missing from the streets.

To estimate ‘missing women,’ we need a baseline. While there are some plausible ‘taste-based’ reasons for the sex ratio on the streets to differ from 50-50, for the current analysis, I assume that in a gender equal society, roughly equal number of men and women are out on the streets. And I attribute any skew to real (and perceived) threat of molestation, violence, harassment, patriarchy (allowing wives, daughters, sisters to go out), discrimination in employment, and similar such things.

Note About Data and Measurement

Of all the people out on the street over the course of a typical day in Delhi, what proportion are women? To answer that, I devised what I thought was a pretty reasonable sampling plan, and a pretty clever data collection strategy see here. Essentially, we would send people at random street locations at random times and ask them to take photos at head height, and then crowd-source counting the total number of people in the picture and the total number of women in the picture.

The data we finally collected in this round bears little resemblance to the original data collection plan. As to why the data collection went off rails, we have nothing to share publicly for now. The map of the places from which we collect data though lays bare the problems.

Data, Scripts, and Analyses are posted here.

Results

The data were collected between 2016-11-12 and 2017-01-11. And between roughly 10 am and 7 pm. In all, we collected nearly 1,958 photos from 196 locations. On average about 81.5% of the people on the street were men. The average proportion of men across various locations was 86.7% which suggests that somewhat busier places have somewhat more women.

Stereotypical Understanding

11 Jul

The paucity of women in Computer Science, Math and Engineering in the US is justly widely lamented. Sometimes, the imbalance is attributed to gender stereotypes. But only a small fraction of men study these fields. And in absolute terms, the proportion of women in these fields is not a great deal lower than the proportion of men. So in some ways, the assertion that these fields are stereotypically male is in itself a misunderstanding.

For greater clarity, a contrived example: Say that the population is split between two similar sized groups, A and B. Say only 1% of Group A members study X, while the proportion of Group B members studying X is 1.5%. This means that 60% of those to study X belong to Group B. Or in more dramatic terms: activity X is stereotypically Group B. However, 98.5% of Group B doesn’t study X. And that number is not a whole lot different from 99%, the percentage of Group A that doesn’t study X.

When people say activity X is stereotypically Group B, many interpret it as ‘activity X is quite popular among X.’ (That is one big stereotype about stereotypes.) That clearly isn’t so. In fact, the difference between the preferences for studying X between Group A and B — as inferred from choices (assuming same choices, utility) — is likely pretty small.

Obliviousness to the point is quite common. For instance, it is behind arguments linking terrorism to Muslims. And Muslims typically respond with a version of the argument laid out above—they note that an overwhelming majority of Muslims are peaceful.

One straightforward conclusion from this exercise is that we may be able to make headway in tackling disciplinary stereotypes by elucidating the point in terms of the difference between p(X|Group A) and p(X| Group B) rather than in terms of p(Group A | X).

(No) Missing daughters of Indian Politicians

29 Jun

Indian politicians get a bad rap. They are thought to be corrupt, inept, and sexist. Here we check whether there is prima facie evidence for sex-selective abortion.

According to data on the Indian Government ‘Archive’, 15th Lok Sabha members (csv) had, in all, 696 sons and 666 daughters for a sex ratio of 957 females to 1000 males. Progeny of members from states with the most skewed sex ratios (Punjab, Haryana, Jammu and Kashmir, and Haryana) had a surprisingly healthy sex ratio of 1245 females to 1000 males. Sex ratios of children of BJP and INC members were 930/1000 and 965/1000 respectively. Rajya Sabha members (csv) had 271 sons and 272 daughters for a sex ratio of 1003 females to 1000 males. Not only was there little evidence of sex-selective abortion, data also suggest that fertility rates were modest. Lok Sabha members had on average 2.5 kids while members of Rajya Sabha had on average 2.2 kids.

Github repository.

p.s. In 2023, I redid the analysis with new official data from 12–17th LS. Results here.

Does Children’s Sex Cause Partisanship?

26 May

More women identify themselves as Democrats than as Republicans. The disparity is yet greater among single women. It is possible (perhaps even likely) that this difference in partisan identification is due to (perceived) policy positions of Republicans and Democrats.

Now let’s do a thought experiment: Imagine a couple about to have a kid. Also, assume that the couple doesn’t engage in sex-selection. Two things can happen – the couple can have a son or a daughter. It is possible that having a daughter persuades the parent to change his or her policy preferences towards a direction that is perceived as more congenial to women. It is also possible that having a son has the opposite impact — persuading parents to adopt more male congenial political preferences. Overall, it is possible that gender of the child makes a difference to parents’ policy preferences. With panel data, one can identify both movements. With cross-sectional data, one can only identify the difference between those who had a son, and those who had a daughter.

Let’s test this using cross-sectional data from Jennings and Stoker’s “Study of Political Socialization: Parent-Child Pairs Based on Survey of Youth Panel and Their Offspring, 1997.”

Let’s assume that a couple’s partisan affiliation doesn’t impact the gender of their kid.

The number of kids, however, is determined by personal choice, which in turn may be impacted by ideology, income, etc. For example, it is likely that conservatives have more kids as they are less likely to believe in contraception, etc. This is also supported by the data. (Ideology is a post-treatment variable. This may not matter if the impact of having a daughter is same in magnitude as the impact of having a son, and if there are similar numbers of each across people.)

Hence, one may conceptualize “treatment” as the gender of the kids, conditional on the number of kids.

Understandably, we only study people who have one or more kids.

Conditional on number of kids, the more daughters respondent has, the less likely respondent is to identify herself as a Republican (b = -.342, p < .01) (when dependent variable is curtailed to Republican/Democrat dichotomous variable; the relationship holds—indeed becomes stronger—if the dependent variable is coded as an ordinal trichotomous variable: Republican, Independent, and Democrat, and an ordered multinomial estimated)

Future:

If what we observe is true then we should also see that as party stances evolve, the impact of gender on policy preference of a parent should vary. One should also be able to do this cross-nationally.

Some other findings:

  1. Probability of having a son (limiting to live births in the U.S.) is about .51. This natural rate varies slightly by income. Daughters are more likely to be born among people with lower incomes. However, the effect of income is extremely modest in the U.S. The live birth ratio is marginally rebalanced by the higher child mortality rate among males. As a result, among 0–21, the ratio between men and women is about equal in U.S.

    In the sample, there are significantly more daughters than sons. The female/male ratio is 1.16. This is ‘significantly’ unusual.

  2. If families are less likely to have kids after the birth of a boy, the number of kids will be negatively correlated with proportion sons. Among people with just one kid, the number of sons is indeed greater than number of daughters, though the difference is insignificant. Overall correlation between proportion sons and number of kids is also very low (corr. = -.041).

Lifting the Veil on Some Issues Around The Burka Debate

30 Mar

For the unfamiliar, the BBC guide to Muslim veils.

The somewhat polemical:
Assuming that God has recommended that women wear the burka, assuming that burka has no impact on a woman’s ability to communicate or quality of life, as has been suggested by its supporters, then here’s a suggestion—to all men, who haven’t been ordered by God to wear a burka, and who don’t see a downside to wearing it—why not voluntarily commit to wearing the burka, since no law opposes such a voluntary act, to show solidarity with the women. My sense is that even the French would come to support the burka if Muslim men en masse chose to wear it.

More considered:
‘The interior ministry says only 1,900 women wear full veils in France, home to Europe’s biggest Muslim minority’ (BBC). If the problem is interpreted solely in terms of women wearing the veil, then it is much smaller than the dust in its wake.

There are three competing concerns at the heart of the debate: Protecting the rights of women who voluntarily want to wear it, protecting the rights of women who are forced to wear it, and protecting (French) ‘culture.’ Setting aside cultural concerns for the moment, let’s focus on the first two claims.

People are incredulous of the claim that women will voluntarily choose to wear something so straightforwardly unpleasant. Even when confronted with a woman who claims to comply voluntarily, they fear coercion, or something akin to brainwashing at play. There is merit to the thought. However, there is much evidence that women subject themselves to many unpleasant things voluntarily, such as wearing high heels (which I understand are uncomfortable to wear). So it is very likely indeed that there is ‘voluntary compliance’ by some women.

Assuming there exist both, voluntary compliers, and those forced to wear the niqab, wouldn’t it be pleasant if we could ensure the rights of both? In fact, doesn’t the extant legal framework provide for such a privilege already? Yes and no, mostly no. While it is true that women forced to wear the niqab can petition the police, it is unlikely to happen for a variety of reasons. Going to the police would mean going against the family, which may mean doing something painful, and risking financial and physical well-being. Additionally, the laws governing such ‘coercion’ are likely to carry modest penalties and unlikely to redress the numerous correlated issues including inadequate financial, and educational opportunities. Many of the issues raised here would seem familiar to people working with domestic abuse, and they are, and the modern state hasn’t (tried to) found a good solution.

Perhaps both camps will agree that wearing a niqab does dramatically limit the career opportunities for women. Of course, people in one of the camps may be happy that there are limits to such opportunities but let’s assume that they would be happy if the women had the same opportunities. Part of the problem here then is the norms of dressing in business environments in the West. Entrepreneurs in Saudi Arabia recently brought to air a television talk show in which both of the hosts wore the niqab. The entire effect was disturbing. However, that isn’t the point. The point is that there may be ways not to reduce career opportunities for women based on the dress code, which after all seems ‘coercive.’

Time considerations mean a fuller consideration of the issue will have to wait. One last point – One of the problems cited about the burka is that it poses a security threat, which has some merit, given its long history in being used a method of escape, including by militant clerics.

War and Sex

11 Nov

War is deadly for both sexes. A missile doesn’t differentiate between a man and a woman. Then, what is the role of gender in war?

Nearly all active militaries in the world have substantially more male soldiers than female soldiers and far more men die on the battlefields than women. But the impact of wars is never limited to artificial battlefields. War enters civilian life through hunger, inadequate health care, the decline in availability of potable water, rape, pillage, and many other ways, reducing life expectancy drastically for both men and women. For example, life expectancy in Afghanistan is 46 years (men), 46 years (women) according to UN figures. The figures hide an important fact that on average women will live longer than men. These figure mean that more women are dying as a result of war than men. These figures still don’t take into account the large number of crimes like rape that are committed predominantly against women.